The Type I Generalized Half Logistic Survival Model

Phillip Oluwatobi Awodutire; Akintayo Kehinde Olapade; Oladapo Adedayo Kolawole

doi:doi:10.11648/j.ijtam.20160202.17

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The Type I Generalized Half Logistic Survival Model

Phillip Oluwatobi Awodutire, Akintayo Kehinde Olapade, Oladapo Adedayo Kolawole

Published in International Journal of Theoretical and Applied Mathematics (Volume 2, Issue 2)

Received: 26 October 2016 Accepted: 10 November 2016 Published: 9 December 2016

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Abstract

In this paper, a three parameter probability distribution function called type I generalized half-logistic distribution is introduced to model survival or time to event data. The survival function, hazard function and median survival time of the survival model were established. Estimation of the parameters of the model was done using the maximum likelihood method. We then applied the type I generalized half-logistic survival model to a breast cancer survival data. The derived result from type I generalized half logistic survival model was compared with the results of some common existing parametric survival models, and this revealed that the type I generalized half-logistic survival model clearly demonstrates superiority over these other models.

Published in	International Journal of Theoretical and Applied Mathematics (Volume 2, Issue 2)
DOI	10.11648/j.ijtam.20160202.17
Page(s)	74-78
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Parameter, Survival Function, Hazard Function, Model, Half Logistic Distribution, Survival Time

References

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[18]	Torabi, H. and Bagheri, F. L. (2010): Estimation of Parameters for an Extended Generalized Half Logistic Distribution Based on Complete Censored data. JIRSS Vol. 9, No. 2, pp 171-19.
[19]	Alireza, A. (2012): Breast Cancer Survival Analysis : Applying the Generalized Gamma Distribution under Different Conditions of the Propotional Hazads and Accelerated Failure Time Assumptions. International Journal of Preventive Medicine, Vol 3, No 9.
[20]	Balakrishnan, N. (1985): Oder statistics from the Half Logistic Distrinution. Journal of Statistics and Computer Smulation, 20, 27-309.
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APA Style

Phillip Oluwatobi Awodutire, Akintayo Kehinde Olapade, Oladapo Adedayo Kolawole. (2016). The Type I Generalized Half Logistic Survival Model. International Journal of Theoretical and Applied Mathematics, 2(2), 74-78. https://doi.org/10.11648/j.ijtam.20160202.17

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ACS Style

Phillip Oluwatobi Awodutire; Akintayo Kehinde Olapade; Oladapo Adedayo Kolawole. The Type I Generalized Half Logistic Survival Model. Int. J. Theor. Appl. Math. 2016, 2(2), 74-78. doi: 10.11648/j.ijtam.20160202.17

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AMA Style

Phillip Oluwatobi Awodutire, Akintayo Kehinde Olapade, Oladapo Adedayo Kolawole. The Type I Generalized Half Logistic Survival Model. Int J Theor Appl Math. 2016;2(2):74-78. doi: 10.11648/j.ijtam.20160202.17

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@article{10.11648/j.ijtam.20160202.17,
  author = {Phillip Oluwatobi Awodutire and Akintayo Kehinde Olapade and Oladapo Adedayo Kolawole},
  title = {The Type I Generalized Half Logistic Survival Model},
  journal = {International Journal of Theoretical and Applied Mathematics},
  volume = {2},
  number = {2},
  pages = {74-78},
  doi = {10.11648/j.ijtam.20160202.17},
  url = {https://doi.org/10.11648/j.ijtam.20160202.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijtam.20160202.17},
  abstract = {In this paper, a three parameter probability distribution function called type I generalized half-logistic distribution is introduced to model survival or time to event data. The survival function, hazard function and median survival time of the survival model were established. Estimation of the parameters of the model was done using the maximum likelihood method. We then applied the type I generalized half-logistic survival model to a breast cancer survival data. The derived result from type I generalized half logistic survival model was compared with the results of some common existing parametric survival models, and this revealed that the type I generalized half-logistic survival model clearly demonstrates superiority over these other models.},
 year = {2016}
}

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TY  - JOUR
T1  - The Type I Generalized Half Logistic Survival Model
AU  - Phillip Oluwatobi Awodutire
AU  - Akintayo Kehinde Olapade
AU  - Oladapo Adedayo Kolawole
Y1  - 2016/12/09
PY  - 2016
N1  - https://doi.org/10.11648/j.ijtam.20160202.17
DO  - 10.11648/j.ijtam.20160202.17
T2  - International Journal of Theoretical and Applied Mathematics
JF  - International Journal of Theoretical and Applied Mathematics
JO  - International Journal of Theoretical and Applied Mathematics
SP  - 74
EP  - 78
PB  - Science Publishing Group
SN  - 2575-5080
UR  - https://doi.org/10.11648/j.ijtam.20160202.17
AB  - In this paper, a three parameter probability distribution function called type I generalized half-logistic distribution is introduced to model survival or time to event data. The survival function, hazard function and median survival time of the survival model were established. Estimation of the parameters of the model was done using the maximum likelihood method. We then applied the type I generalized half-logistic survival model to a breast cancer survival data. The derived result from type I generalized half logistic survival model was compared with the results of some common existing parametric survival models, and this revealed that the type I generalized half-logistic survival model clearly demonstrates superiority over these other models.
VL  - 2
IS  - 2
ER  -

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Author Information

Phillip Oluwatobi Awodutire

Department of Statistics, Federal Polytechnic of Oil and Gas, Bonny, Nigeria
Akintayo Kehinde Olapade

Department of Mathematics, Obafemi Awolowo University, Ile-Ife, Nigeria
Oladapo Adedayo Kolawole

Department of Surgery, Ladoke Akintola University of Technology Teaching Hospital, Osogbo, Nigeria

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Plain Text BibTeX RIS

APA Style

Phillip Oluwatobi Awodutire, Akintayo Kehinde Olapade, Oladapo Adedayo Kolawole. (2016). The Type I Generalized Half Logistic Survival Model. International Journal of Theoretical and Applied Mathematics, 2(2), 74-78. https://doi.org/10.11648/j.ijtam.20160202.17

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ACS Style

Phillip Oluwatobi Awodutire; Akintayo Kehinde Olapade; Oladapo Adedayo Kolawole. The Type I Generalized Half Logistic Survival Model. Int. J. Theor. Appl. Math. 2016, 2(2), 74-78. doi: 10.11648/j.ijtam.20160202.17

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AMA Style

Phillip Oluwatobi Awodutire, Akintayo Kehinde Olapade, Oladapo Adedayo Kolawole. The Type I Generalized Half Logistic Survival Model. Int J Theor Appl Math. 2016;2(2):74-78. doi: 10.11648/j.ijtam.20160202.17

Copy | Download

@article{10.11648/j.ijtam.20160202.17,
  author = {Phillip Oluwatobi Awodutire and Akintayo Kehinde Olapade and Oladapo Adedayo Kolawole},
  title = {The Type I Generalized Half Logistic Survival Model},
  journal = {International Journal of Theoretical and Applied Mathematics},
  volume = {2},
  number = {2},
  pages = {74-78},
  doi = {10.11648/j.ijtam.20160202.17},
  url = {https://doi.org/10.11648/j.ijtam.20160202.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijtam.20160202.17},
  abstract = {In this paper, a three parameter probability distribution function called type I generalized half-logistic distribution is introduced to model survival or time to event data. The survival function, hazard function and median survival time of the survival model were established. Estimation of the parameters of the model was done using the maximum likelihood method. We then applied the type I generalized half-logistic survival model to a breast cancer survival data. The derived result from type I generalized half logistic survival model was compared with the results of some common existing parametric survival models, and this revealed that the type I generalized half-logistic survival model clearly demonstrates superiority over these other models.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - The Type I Generalized Half Logistic Survival Model
AU  - Phillip Oluwatobi Awodutire
AU  - Akintayo Kehinde Olapade
AU  - Oladapo Adedayo Kolawole
Y1  - 2016/12/09
PY  - 2016
N1  - https://doi.org/10.11648/j.ijtam.20160202.17
DO  - 10.11648/j.ijtam.20160202.17
T2  - International Journal of Theoretical and Applied Mathematics
JF  - International Journal of Theoretical and Applied Mathematics
JO  - International Journal of Theoretical and Applied Mathematics
SP  - 74
EP  - 78
PB  - Science Publishing Group
SN  - 2575-5080
UR  - https://doi.org/10.11648/j.ijtam.20160202.17
AB  - In this paper, a three parameter probability distribution function called type I generalized half-logistic distribution is introduced to model survival or time to event data. The survival function, hazard function and median survival time of the survival model were established. Estimation of the parameters of the model was done using the maximum likelihood method. We then applied the type I generalized half-logistic survival model to a breast cancer survival data. The derived result from type I generalized half logistic survival model was compared with the results of some common existing parametric survival models, and this revealed that the type I generalized half-logistic survival model clearly demonstrates superiority over these other models.
VL  - 2
IS  - 2
ER  -

Copy | Download